How to Improve Flight Booking with Personalized Search

It is no longer enough to display flight results to provide air travelers with a seamless search experience.

Airlines and travel brands must be aware of how customers search for a flight, when, where, and what is truly motivating them.

Here’s a series of recommendations to create as smart search experience for users booking a flight.

According to the Expedia blog, a typical customer searches up to 48 times before booking a flight. That’s quite a demanding effort for an eager traveler. Your goal, as a travel brand, is to decrease this initial anxiety and help them find what they’re looking for.

Travelers like to think they have a trick or strategy for finding the best airfare, but in reality we are all searching for and reserving tickets in similar fashion.

The emergence of machine learning technologies has led the Travel Industry to rethink Search in creatives ways. The use of Natural Language Processing (NLP), from “Search-Anything” fields to Chatbots, is facilitating the task of making booking a personalized experience.

How Air Travelers Typically Search for a Flight

The average North American consumer searches for a flight through websites (not apps.) This is an overwhelming fact according to the Portrait of an American Traveler.

It’s interesting to note that travelers booking a quick getaway will purchase tickets a month before departure, while those booking a short vacation will purchase tickets three to six months in advance.

This is only part of the picture. Researchers at Expedia noticed that people write down on a piece of paper relevant results they encounter across dozens of searches, despite having other technological advances available.

Helping the user to easily find the right option sooner can be accomplished by reducing the amount of results presented based on previous searches.

Recommendations for a Personalized Search

Expedia continuously fine tunes their algorithms to present only relevant results based on real purchasing patterns.

Here’s a list of recommendations based on how they did it,

Be smart with the predictions on the search box, e.g. probably Paris means Paris, France and not Paris, Texas.

Track how they make combinations of alternate airports and dates in those searches.

Look for similar deltas for departure and arrival days and surface them as search recommendations.

Display relevant recommendations at a glance, so they can choose between price or convenience.

Track the effectiveness, value, and accuracy of the prediction against real booking information. Adjust them to best benefit your customers.

Finding the right flight is a hard computational problem because airlines adjust prices many times a day which frustrates caching. This blog article describes how to address the problem of deciding which flights to show and then ensuring the pricing is accurate, since they are not independent problems.

Finding the right flight is also a cumbersome task for users. Consider a typical search from Seattle to Miami, there might be millions of flights available if you take into consideration the components of alternate airports and dates but also price range.

However, tracking those very same combinations might provide you with a hint on how to improve search results. The challenge is to present recommendations that are not solely based on a snapshot of the saved price but in a way that is dynamically evolving.

Using Chatbots as Concierges

Chatbots are a great way to help users on their quest for the right flight. They are still evolving and it’s not clear how they might aid along the long funnel that is travel e-commerce.

Chatbots will become a commonplace in the upcoming years, simply because 24-hour service assistance is a must in a world that never sleeps.

Here are some high level recommendations to design your first chatbot,

They must solve a very specific customer problem or need. It’s impossible to have a chatbot to aid the user at every single step of the travel funnel. E.g. Searching flight options on different airlines, booking a flight, printing tickets, tracking flights, etc.

Make it conversational. Their responses must feel as if one was chatting with a friend. Chatbots are a great opportunity to give your brand a voice. You might even include a joke or two.

Use Natural Processing Language, simply put, NPL is the ability of computers to understand human language as it’s spoken or written. Small changes to the way a chatbot “speaks” can have huge impact on customer behaviour.

It is very important that the experience feels natural, so picking the right channel where the chatbot will exist is paramount. Options range from being embedded on Facebook messenger, Skype, the company’s website or an application. The chatbot should be accessible in the context where your target audience usually spends their time.

Making a More Pleasant Search Experience

Finding and booking a flight is the very beginning of the travel experience funnel. It is a stage characterized by subjectivity where travelers have multiple factors to take into account. They might be unsure of most of them, i.e. the exact date, destination, budget, airports, etc.

During this research phase, the regular travelers make multiple combinations of the variables above until they make their final decision. Usually, business travelers and frequent flyers require less assistance, as they tend to know for sure what they’re looking for.

In both cases, providing them with only relevant flight options through smart search engines and making personalized recommendations that reflect real-time airline fare, might make the experience more pleasant.